Smartphone filters equipped with face recognition, Google making informed predictions, and Email smartly filtering spam on a daily basis – we are closer to an AI takeover than we think.
Artificial Intelligence has integrated itself into our daily lives slowly but surely. From AI-powered inhalers to intelligent chatbots and smart camera systems, the modern day consumer is growing used to smart electronics. As more and more devices become intelligent, there is an increasing need for computing power in the form of data centers and cloud infrastructures. However, if we continue at this rate, soon there will be a shortage of data centers capable of sending the growing mass of data to the cloud.
Giving AI An Edge
Machine Learning is a widely used branch of AI which makes use of intelligent algorithms to learn patterns in available data. Building an AI model is a computationally expensive task that is usually done over the cloud. However, due to the increase in the use of AI, hardware distributors worldwide are equipping devices such as smartphones with their own ML-capable chips.
This is what makes an Edge AI device a success. With the capability to run ML workloads on-site instead of sending the data to the cloud, these smart devices can reduce costs, improve performance and minimize response times.
Boost Performance and Speed
The average user is looking to get important information in the blink of an eye. But smart devices can be slowed down by the transfer of information to and from the cloud. On-device AI can cut down on response times by processing data on-site to ensure a boost in performance.
Improve Privacy and Security
Despite the growing popularity of the cloud, cloud security is still a huge concern for businesses all around the world. Storing data on the cloud creates centralization that can easily be exploited by hackers and malicious entities. To avoid this multimillion dollar mishap, businesses have to ensure that critical data always stays on the device belongs to. By safeguarding data on a single device instead of sending it to the cloud, on-device AI can improve privacy standards and strengthen security.
For many businesses, managing the costs associated with cloud infrastructure is a challenge. Consequently, many businesses which lack AI-driven solutions are afraid of the high costs it might incur. On-device AI can mitigate these concerns by cutting down the costs of managing a cloud infrastructure.
As AI-powered technology moves towards making life easier in all aspects, computational needs will continue to increase exponentially. Edge devices can help bridge the gap and empower smart devices, but only if used with the right programming approaches and platform.